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Record W2758153481 · doi:10.18632/oncotarget.21352

Eyes absent gene (EYA1) is a pathogenic driver and a therapeutic target for melanoma

2017· article· en· W2758153481 on OpenAlexaffabout
Joshua Zhou, Yuanshen Huang, Xue Zhang, Yabin Cheng, Liren Tang, Xiaodong Ma

Bibliographic record

VenueOncotarget · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsWelichem Biotech (Canada)University of British Columbia
Fundersnot available
KeywordsMedicineMelanomaCancer researchGeneBioinformaticsOncologyGeneticsBiology

Abstract

fetched live from OpenAlex

// Joshua Jiawei Zhou 1, 2 , Yuanshen Huang 3 , Xue Zhang 3 , Yabin Cheng 4 , Liren Tang 2 and Xiaodong Ma 5 1 Department of Anesthesiology, Pharmacology, and Therapeutics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada 2 Welichem Biotech Inc., Burnaby, BC, Canada 3 Department of Dermatology and Skin Science, University of British Columbia, Vancouver, BC, Canada 4 School of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian, China 5 College of Pharmacology, Dalian Medical University, Dalian, Liaoning Province, China Correspondence to: Liren Tang, email: lirentang@yahoo.com Xiaodong Ma, email: xiaodong.ma@139.com Yabin Cheng, email: chengyb@xmu.edu.cn Keywords: melanoma, biomarker, EYA1, chromatin remodeling, benzbromarone Received: June 01, 2017      Accepted: August 28, 2017      Published: September 27, 2017 ABSTRACT EYA1 is a DNA repair enzyme that is induced after DNA damage and is upregulated in melanoma. However, its role in pathogenesis and therapeutic targeting of melanoma is unknown. Our objectives are (1) to study the relationship between EYA1 expression levels and melanoma patients’ clinical pathologic parameters including survival; (2) to investigate its impact on cultured melanoma cells in vitro ; and (3) to evaluate EYA1 inhibitors’ potential as a treatment of melanoma. Melanoma tissue microarrays were used to assess EYA1 protein expression in 326 melanoma tissues, and to correlate the expression with patients’ clinical pathological parameters. In addition, retroviral ShRNA vectors were used to silence expression of EYA1 in A375 melanoma cells, and the resultant cells examined for changes in growth, DNA synthesis, and tumor formation in vitro . Lastly, melanoma cells were treated with benzbromarone with or without the BRAF inhibitor vemurafenib. Our results showed that EYA1 protein is low in benign nevi, but is significantly up-regulated in melanoma in situ , and remains high in invasive and metastatic melanoma. In addition, silencing of EYA1 gene expression resulted in decreased proliferation and colony formation. These were associated with decreased cyclin D1 and increased phosphorylated histone protein γH2AX. Finally, treatment with benzbromarone, a specific inhibitor of EYA1, caused significant inhibition of melanoma cell proliferation, and increased sensitivity to the BRAF inhibitor vemurafenib. In conclusion, EYA1 gene is a pathogenic driver in melanoma pathogenesis. Targeting EYA1 may be a valuable strategy for treatment of melanoma.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.267
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2017
Admission routes2
Has abstractyes

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